Since the establishment of the hybridoma technology (1), a vast repertoire of murine monoclonal antibodies (mAbs) have been generated and characterized. Many of them have been applied in diagnosis of human diseases, such as cancers, infectious diseases, autoimmune diseases, etc. Their clinical use in the treatment of diseases, however, is limited mainly because the murine mAbs elicit human anti-murine antibodies (HAMA) responses in patients (2). The HAMA response occurred in up to 50% of patients upon administration of murine hybridoma-derived antibodies (3) and this has severely compromised the safety, efficacy, and biological half-life of these reagents. In addition, murine antibody constant regions are inefficient in directing suitable human immune effector functions for therapeutic effects. Efforts to produce human antibodies by hybridoma technology (4) and Epstein-Barr virus (EBV)-mediated B-lymphocyte transformation (5) have met with limited success. Their widespread application is hampered by the lack of robust human hybridoma fusion partners and the instability of EBV-transformed clones, respectively (6). As a means of circumventing the limitations of non-human mAbs and human antibodies, several strategies have been developed to convert non-human antibody sequences into human antibody sequences, a process termed antibody humanization, to exploit the non-human mAbs against a variety of human disease targets and turn them into effective therapeutic reagents.
Two major approaches have been used to transform murine antibodies into humanized antibodies: rational design and empirical methods. The rational design methods are characterized by antibody structural modeling, generating a few variants of the engineered antibodies and assessing their binding or any other property of interest. If the designed variants do not produce the expected results, a new cycle of design and binding assessment is initiated. The rational design methods include, but are not limited to, complementarity determining region (CDR) grafting, resurfacing, super-humanization and human string content optimization, among which, CDR grafting is the most widely used. Humanized antibody generated by CDR-grafting contains amino acids from the six CDRs of the parental murine mAb, which are grafted onto a human antibody framework. The low content of non-human sequence in humanized antibodies (˜5%) has proven effective in both reducing the immunogenicity and prolonging the serum half-life in humans (7).
Unfortunately, simple grafting of CDR sequences often yields humanized antibodies that bind antigen much more weakly than the parental murine mAb, and decreases in affinity of up to several hundred-fold have been reported (Eigenbrot et al., 1994, Proteins 18, 49-62). To restore high affinity, the antibody must be further engineered to fine tune the structure of the antigen-binding loops. This is usually achieved by replacing key residues in the framework regions of the antibody variable domains with the matching sequence from the parental murine antibody. These framework residues are usually involved in supporting the conformation of the CDR loops, although some framework residues may themselves directly contact the antigen (Mian et al., 1991, J Mol Biol 217, 133-151). It has become apparent that the accomplishment of antibody humanization by rational method faces relatively high uncertainty. Moreover, broad application of this technology has also been restricted due to reliance on structural biology, which is not readily available for many laboratories.
In contrast to the rational design methods, empirical methods do not require the structure information of the antibody. They depend on the generation of large combinatorial libraries and selection of the desired variants by enrichment technologies such as phage, ribosome or yeast display, or by high throughput screening techniques. These methods rest on selection rather than making assumptions on the impact of mutations on the antibody structure. These methods include, but are not limited to, framework libraries, guided selection, framework shuffling and humaneering. However, the success of these methods relies mainly on the construction of large libraries, because high affinity antibodies can be isolated from the large size of antibody repertoires.
Antibody humanization is the core technology in antibody drug development. Although the first humanized antibody was generated decades ago, antibody humanization still faces many technology challenges.
There is a need of an improved method for antibody humanization. The present invention relates to such a method as well as humanized antibodies made by such a method.